边根庆, 王月. 一种基于矩阵和权重改进的Apriori算法[J]. 微电子学与计算机, 2017, 34(1): 136-140.
引用本文: 边根庆, 王月. 一种基于矩阵和权重改进的Apriori算法[J]. 微电子学与计算机, 2017, 34(1): 136-140.
BIAN Gen-qing, WANG Yue. An Improved Apriori Algorithm Based Matrix and Weight[J]. Microelectronics & Computer, 2017, 34(1): 136-140.
Citation: BIAN Gen-qing, WANG Yue. An Improved Apriori Algorithm Based Matrix and Weight[J]. Microelectronics & Computer, 2017, 34(1): 136-140.

一种基于矩阵和权重改进的Apriori算法

An Improved Apriori Algorithm Based Matrix and Weight

  • 摘要: 提出基于矩阵和权重的一种改进算法——MW_Apriori算法.该算法首先通过扫描一次事务数据库来构造0-1事务矩阵, 其次赋予项和事务权重, 并计算项的权重支持度, 从而得到频繁项集.实验结果表明, MW_Apriori算法避免了数据库的重复扫描, 使得时间和空间的耗费显著减少, 同时能有效地挖掘出隐藏的、更有价值的事件.

     

    Abstract: An improved algorithm, which is called MW_Apriori algorithm is proposed based on the matrix and weight in this paper.Firstly, build the 0-1transaction matrix by scanning transaction database.Then items and transactions are assigned to weights, and the weighted support of items are caculated, accordingly gettig the frequent itemsets.Experiments show that MW_Apriori algorithm avoids rescanning the database, making the cost of time and space significantly reduced, at the same time can effectively mine the hidden and valuable rare events.

     

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